The SETL2 programming language is a very high level language based on the theory and notation of finite sets. It is evolved from SETL, developed at New York University by J. T. Schwartz. SETL2 adds to SETL a syntax and name scoping closer to more recent imperative languages, full block structure, and procedures as first class objects. This document is divided into three parts: First, we give an introduction to SETL2, highlighting its differences from SETL. A description of programming with sets along with a detailed description of SETL is given in [SDDS86], and we strongly encourage the reader to refer to that book if he has no experience with SETL. The second part of this document provides a detailed reference manual of the SETL2 language. The final section is a guide to the operation of the current implementations of SETL2. This paper is Technical Report 490, Courant Institute of Mathematical Sciences, New York University. New York University Department of Computer Scien...

ion for Expressing Array Computation Bradford L. Chamberlain E Christopher Lewis Calvin Lin + Lawrence Snyder University of Washington, Seattle, WA 98195-2350 + University of Texas, Austin, TX 78712 fbrad,echris,snyderg@cs.washington.edu, lin@cs.utexas.edu Abstract Most array languages, such as Fortran 90, Matlab, and APL, provide support for referencing arrays by extending the traditional array subscripting construct found in scalar languages. We present an alternative approach that exploits the concept of regions---a representation of index sets that can be named, manipulated with high-level operators, and syntactically separated from array references. This paper develops the concept of region-based programming and describes its benefits in the context of an idealized array language called RL. We show that regions simplify programming, reduce the likelihood of errors, and enable code reuse. Furthermore, we describe how regions accentuate the locality of array expressions and h...

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Artificial neural networks (ANN's), due to their inherent parallelism, offer an attractive paradigm for implementation of symbol processing systems for applications in computer science and artificial intelligence. This paper explores systematic synthesis of modular neural-network architectures for syntax analysis using a prespecified grammar---a prototypical symbol processing task which finds applications in programming language interpretation, syntax analysis of symbolic expressions, and high-performance compilers. The proposed architecture is assembled from ANN components for lexical analysis, stack, parsing and parse tree construction. Each of these modules takes advantage of parallel content-based pattern matching using a neural associative memory. The proposed neural-network architecture for syntax analysis provides a relatively efficient and high performance alternative to current computer systems for applications that involve parsing of LR grammars which constitute a widely used subset of deterministic context-free grammars. Comparison of quantitatively estimated performance of such a system [implemented using current CMOS very large scale integration (VLSI) technology] with that of conventional computers demonstrates the benefits of massively parallel neuralnetwork architectures for symbol processing applications.

Through the use of interpreters it is possible to teach programming languages in an analytic way without the mathematical overhead associated with other formal methods. This is a natural evolution of programming language pedagogy from present approaches that are largely descriptive. As a bonus, students receive training in the use of meta-linguistic abstraction in program design. An example of this approach is presented along with suggested variations and discussion of a number of practical considerations that may be crucial to success in the classroom. Introduction Early texts in the study of programming languages were descriptive of a variety of programming languages. By surveying a variety of language types they provided exposure to a number of language principles, but they were organized around languages, not principles. The next generation of programming language texts were organized around underlying principles, but they were still descriptive. Principles were described informal...

Recognising language design as a valid programming paradigm should have widespread benefits e.g. for the development of CASE tools. This validity is demonstrated both pragmatically and formally. The pragmatic justification derives from matching the patterns of usage and quality assessment of programming languages on the one hand, with corresponding patterns for the output of the "programming" activity. The formal justification derives from an examination of denotational semantics. Language design as incarnated in the production of a denotational semantics is evidently functional programming, with all the concerns for modularity and abstraction that should also be the concerns of applications programmers. Then, when the denotational equations are restructured in better accord with these programming principles, it emerges that the semantics of a centrepiece of programmer activity - declarations - are evidently language extensions. 1 Introduction An earlier treatment [1] established th...

The programming walkthrough is a method for assessing how easy or hard...

Undergraduate computer science students typically have only a limited understanding of their favorite languages and no inkling of other programming paradigms. Yet modern programmers typically work with several languages, and the availability of cheap concurrency is exposing fundamental problems in standard concurrent programming techniques (mutable objects and threads). This situation presents a great opportunity: by exploring nonstandard techniques for gaining intellectual control over concurrent programs, one can motivate and teach important semantic concepts (such as scoping) and important programming concepts (such as functional abstraction). Such a curriculum stimulates student interest in exploring new programming paradigms.

Handout written by Maggie Johnson and revised by Julie Zelenski.